Data Management Analyst

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Job description

Job Description:

• Cleansing means identifying data that is critical and defining the data in critical terms. Extracting business rules from the critical data and then using the business rules to generate quality insights. Ex: Identifying the data that is critical - present screenshots of the data to understand what the most critical data is.
• Predominately Agile environment but have not entirely eliminated Waterfall
• Provide Data Management guidance to key BP Transformation programs, helping our businesses improve the way they create, maintain, and use their data
• Partner with key Business Data and IT Systems SMEs to identify data that is critical to the success of BP's digital transformation programs (Critical Data Elements)
• Capture metadata and business rule requirements for critical data and metrics
• Profile data using business rules to establish data quality insights and ongoing quality metrics
• Establish preventative and detective data quality controls, both technical and operational
• Perform root cause analysis for and drive the resolution of complex data quality issues
• Identify Master and Reference data opportunities to further advance BP's data management agenda
• Facilitate collaboration and lead project conversations regarding data-change impact analysis, to mitigate risks to our data supply chain. (Data Change Management)
• Help establish and maintain data related policies, processes, standards, and frameworks
• Simplify complex or foreign data concepts to communicate work in a way that resonates with business teammates

Qualifications:

• Advanced SQL Data Query experience
• Ability to understand the story the data is telling
• Being adept enough to conceptualize data quality rules for the business
• Familiarity with data profiling tools (Talend, SAS Vaya or Dataflux, TOAD, or Oracle SQL Developer)
• Demonstrated application of core Data Management principles with little or no supervision: Metadata Management, Data Quality Management, Data Stewardship, Data Change Management, Data Governance, and Master/Reference Data Management
• Established hands-on technical proficiency with data, querying databases, data profiling, data quality analysis, data cleansing, and data validation using tools like Talend, SAS Vaya or Dataflux, TOAD, or Oracle SQL Developer
• Strong analytical and problem‐solving capabilities, including the ability to clearly define problems, collect data from a variety of sources, establish facts, draw valid/profitable conclusions, and influence others through effective communication